---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2 russian
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-russian

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2972
- Wer: 0.4920

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.6885        | 0.25  | 500   | 1.2398          | 0.4926 |
| 0.6499        | 0.5   | 1000  | 1.2338          | 0.4957 |
| 0.6446        | 0.74  | 1500  | 1.2716          | 0.4975 |
| 0.6966        | 0.99  | 2000  | 1.5439          | 0.4942 |
| 0.7188        | 1.24  | 2500  | 1.4889          | 0.4960 |
| 0.7116        | 1.49  | 3000  | 1.0075          | 0.4921 |
| 0.7178        | 1.73  | 3500  | 1.3123          | 0.4984 |
| 0.7034        | 1.98  | 4000  | 1.1037          | 0.4919 |
| 0.7116        | 2.23  | 4500  | 0.9947          | 0.4942 |
| 0.7203        | 2.48  | 5000  | 1.1547          | 0.4940 |
| 0.72          | 2.73  | 5500  | 1.1245          | 0.4960 |
| 0.6921        | 2.97  | 6000  | 1.0844          | 0.4947 |
| 0.702         | 3.22  | 6500  | 1.1999          | 0.4931 |
| 0.6965        | 3.47  | 7000  | 1.2106          | 0.4906 |
| 0.6928        | 3.72  | 7500  | 1.1275          | 0.4939 |
| 0.6973        | 3.96  | 8000  | 1.1953          | 0.4922 |
| 0.7065        | 4.21  | 8500  | 1.2046          | 0.4931 |
| 0.6921        | 4.46  | 9000  | 1.2052          | 0.4926 |
| 0.6977        | 4.71  | 9500  | 1.2806          | 0.4922 |
| 0.688         | 4.96  | 10000 | 1.3327          | 0.4926 |
| 0.7003        | 5.2   | 10500 | 1.3518          | 0.4930 |
| 0.6981        | 5.45  | 11000 | 1.3295          | 0.4936 |
| 0.6913        | 5.7   | 11500 | 1.3065          | 0.4928 |
| 0.6822        | 5.95  | 12000 | 1.2972          | 0.4920 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6